These conflicts are an example of how difficult progress can be when it causes obsolescence of something we consider dear or sacred. Is there a more quintessential image of human character than a farmer's intimate relationship with the sight, smell, and feel of his dirt? Monsanto has technology that makes this knowledge increasingly obsolete. Likewise, AI diagnosticians are becoming more dependable than doctors and nurses.

Our reaction to this is much different than our reaction to the obsolescence of technology. Or, even think of cars replacing horses. Stable keepers' unions probably had ads against those infernal new machines, but with distance, we recognize these advances as boons to human opportunity. (Auto repair diagnosis has also become highly automated. I think it is an interesting exercise to compare this to medical automation. There was relatively little despair over this development in auto repair. How does this relate to our feelings toward this service, and toward auto mechanics versus doctors and nurses?)

It seems compassionate and pro-human - pro-community - to support the skilled farmers and professionals in these matters. The sentiments being prodded in the nurse and musician ads are universally sensitive. And, come on, are you really going to side with Monsanto over farmers? Is it outrageous and mean spirited of me to feel disappointment that our educational institutions are shielding teachers from these same pressures?

But, the irony is that these easy sentimental biases are wholly anti-progress. If we apply them in these contexts, we are allowing our subconscious knack for social signaling to overbear progress in the very society we are signaling to. We have a bias for supporting obsolete human capital because it shows our loyalty and support for people doing good in our communities. It shows our sophistication - that we can recognize talent and skill.

But, what are the consequences? In the end, the most powerful force for improvement of the most poor, the most egalitarian tool in the history of humanity, is automation. Canned music means that paupers can now enjoy the same entertainment previously only available to the elite. AI medical tools will mean that the triage office in rural Appalachia or the Kenyan savannah will offer the same quality of diagnosis as the Mayo Clinic. Farming automation means that basic foodstuffs are abundant for many poor people across the globe. Imagine the possibilities for marginalized kids if teaching were largely automated. Not only would the poorest kids have access to the same sources of knowledge as middle class kids, but resources would be freed to provide them with even more services.

A central dilemma of political advocacy: Being truly pro-progress sometimes necessarily means taking postures that make you look like an ass. ("Don't you see? We're all better off because the skills you built over a lifetime in a widely honored craft are no longer needed! Huzzah!") Of course, also being human means that if you commit to this discipline, sometimes you will bravely be defending progress at your own social cost, and sometimes, you will just be being an ass. Since these matters can never be universally determined with certainty, not looking like an ass is probably the smart choice most of the time. Thus, I would humbly suggest that, if your economics or politics don't frequently put you in the unavoidable position of supporting positions only an ass would support, you might just be a cog in a giant collective action problem. But, I suppose I could just be saying that because I'm an ass.

Tuesday, May 27, 2014

My point was that this historical relationship seemed pretty linear and stable, and for the number of workers at $10.10 or less without a binding minimum wage to be twice the number that there are with a binding minimum wage, there would have to be significant distortions in the labor force, probably including measurable disemployment.

Menzie Chinn, at www.econbrowser.com looked at the relationship here. Using Durbin-Watson and other tests, he found that the correlation could be spurious because of a lack of stationarity. There is a trend break at Minimum Wage levels below about 27% of the Average Wage (MW/AW), which I think is because the legal minimum begins to fall below the natural minimum wage in that range. But, cutting the data off before 2001 doesn't seem to help much on the Durbin-Watson test.

So, clearly, there is a positive relationship between these ratios, but the coefficient (shown as .30 in the graph) may be suspect. Because of Dr. Chinn's input, I also looked again at the EPI data that I had originally referenced, and realized that there was updated data as well as a couple of additional data points that I could add to the graph.

I looked at the same data from my original post, but as annual changes instead of as levels over time. Residual autocorrelation and stationarity aren't issues in this data if we use yearly changes instead of levels. Here are graphs of the annual changes over time and scatter plots of the annual change in the ratios. The first scatter plot is of the entire period. The second scatter plot is of the period 1981-2001. This cuts out the period after 2001 during which the legal MW was too low to exert typical influence and 1980, which is an outlier. Culling the data down to this period pulls the slope coefficient up to .378.

The final, large graph below compares historical MW employment with (1) the estimated level of MW employment using the coefficient from the yearly changes, (2) the estimated total number of MW workers plus workers not employed due to the MW (based on my estimate of a loss of 0.26% in total employment for each 1% increase in the MW/AW ratio), and (3) three EPI estimates of the number of workers at or below their proposed MW levels in 2014, 2015, and 2016.

EPI assumes no job loss (and, in fact, some job gains), so I would interpret the difference between the EPI estimates of MW workers and my estimate of the number of workers as a combination of:
(1) Job losers captured by my estimate.
(2) Job losers not captured by my estimate.
(3) Workers currently under the EPI proposed MW levels who would have new wage levels slightly above the MW after implementation.
(4) Job gains incorrectly assumed by EPI.

This is not an exhaustive list, but these seem like an obvious starting point. Of course, there is a possibility that I have over-estimated the job losers, and there are other explanations for the gap.

If I understand him correctly, Dr. Chinn believes that there has been a shift in the distribution of low wage workers, so that, even though the coefficient of the slope of this relationship appears to have been below 0.5 in the past, it is currently much higher. In other words, an increasing MW level will sweep up many more workers than it had in the past. So, he sees the relationship implied from the EPI estimates of an increase of about 1% in the MW workers/Total Labor Force ratio as a reasonable possibility of the number of workers who would be working at a minimum wage for each 1% rise in the ratio of MW/AW.

It seems possible that this thesis could be tested now, if there is a set of data somewhere that compares the distribution of wages today with the distribution of wages in about 1989. The minimum wage was in the same ballpark then as it is today, as a percentage of the average wage, so if there had been an exogenous shift in wage distribution, a comparison of those two sets would be informative.

But, what I think might be the most interesting aspect of this is how our priors feed into our interpretations of events in complex ways that prevent the data itself from creating an agreed upon measure.

To me, this graph is predictable. I would expect MW legislation to create disemployment. So, if we are measuring the number of workers earning less than 35% of the average wage, I would expect to see many more of them when the MW/AW ratio is only 25% than when the MW/AW ratio is 35%. So, the EPI estimates seem fairly predictable to me, and the question comes down to how much will employment at the new MW level decrease as we raise the MW to that level - a question which this basic analysis might begin to crawl toward.

To someone who doesn't think that MW legislation creates disemployment, the number of workers earning 35% or less of the average wage should be relatively unchanged in any context where the MW/AW ratio is at or below 35%. So, a large increase in low wage workers that just happened to coincide with a decreasing MW/AW level would appear to be an exogenous change to the labor market. Since the decreasing MW level wouldn't seem like an explanation for increasing low wage employment, this increase in low wage employment would be bad news. It would signal that wages are becoming more inequitable, divided between upper and lower classes. It would signal an economy only creating low-wage, low-quality working opportunities. These exogenous changes in the labor market would mean that many more workers would be affected by an increase in the minimum wage, and since the minimum wage would, on net, be beneficial to low wage workers, this would be a compassionate policy to implement, as a response to the shifting distribution of wages.

This seems like an issue that could finally be settled empirically, but previous federal increases in the minimum wage have, unfortunately, coincided with apparently exogenous labor crises. This has happened with such regularity that we can't rule out the fact that Congress' motivation to increase the minimum wage is somehow correlated with some third variable that correlates both with Congress' motivation for raising MW and with labor crises. After 60 years of this pattern, it seems unlikely to change, whether the minimum wage is the cause of job losses or not. Of course, if I thought MW hikes were defensible, I would still recommend them as a policy prescription. I would feel a duty to support positive policies, and Congress' knack for bad timing would be a problem for someone else to solve separately.

My last post discussed trends in Commercial and Industrial Loans as a proportion of total bank credit (chart 1). One obvious issue in that graph is the tremendous drop in C&I Loans over time.

Interestingly, the level of C&I Loans as a proportion of GDP is pretty level over many decades (chart 2).

Chart 2

So, the change isn't so much a product of decreasing C&I Loans as it is of Increasing Bank Credit in general. Chart 3 shows securities in bank credit (treasuries and federal agency bonds) as a proportion of GDP (inverted), compared to inflation rates. These proportions seem to move with inflation and nominal rates. As rates decrease, securities in bank credit increase.
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Chart 3

Here is an old article, by Frank Steindl, discussing how cash and bonds could interact as Giffen goods. Alternatively, Scott Sumner frequently discusses how the opportunity cost of holding cash is higher when rates are high, so as rates go up, central banks can actually reduce their asset bases, counterintuitively. I don't know if this is precisely the description of a Giffen good, but it does mean that the more money a central bank produces, the less of it the market will demand. Recently, there has been mention of treasuries as Giffen goods, with regard to default risk. Here is an Economist article that suggests the flight from risk is so strong that high public debt and sovereign default risk can actually increase demand for U.S. Treasuries. Treasuries would be a Giffen good.
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Chart 4

I believe all of these explanations of Treasury bonds as Giffen goods have some merit. But, looking at C&I Loans got me thinking about bonds as a Giffen good from a slightly different perspective. Chart 4 shows the relative change in the level of C&I Loans, real estate loans, securities in bank credit, and currency in circulation, over time, as proportions of GDP. (Real estate loans are slightly complicated by a long term positive trend.) Currency, securities, and real estate all show an inverse relationship to inflation & nominal rates.

Currency can be explained by Scott Sumner's point, that the market is more indifferent about holding cash when rates are low.

Chart 5

But, I think what real estate and bank securities have in common is that they are low risk long term cash flow instruments. Their nominal rate levels are relatively low because of low credit risk, but they do have duration risk. The longer the duration of a bond, the more vulnerable it is to changes in interest rates. Prices and yields are inversely proportional, which means that as yields get lower, the price becomes more sensitive to yield changes (chart 5). In other words, as rates decrease, bonds get riskier. But, since real estate and government bonds are the least risky parts of bank balance sheets, banks might react to this higher risk by accumulating more of these assets. When the price of these low risk bonds goes up, their risk goes up, and when their risk goes up, banks want more low-risk assets. We can intuit how the hierarchy of risk in a bank's or a household's balance sheet would begin with low risk assets and add higher risk assets as conditions allow. These assets aren't exactly what we would call an inferior good, yet their place in balance sheet construction would be parallel.
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I have discussed how the Price to Rent ratio for homes should increase as real interest rates decrease. This can happen through an increase in price or a decrease in rents. In practice, it appears to have come entirely from increases in real estate prices. Could it be because low risk long term securities are Giffen goods? As their values increase, the economy's propensity to hold them also increases, whether in terms of ownership of properties or bank ownership of securities.

PS. Here is a chart from this Economist article. At that site the chart is interactive. Note that house prices across the Anglosphere have followed similar trajectories for the last 40 years, until 2008. Since then, the US is the outlier. It is tempting to think that the US has reverted back to a normal valuation level, but I think this is a product of mental accounting biases. If US home prices recover to pre-crisis levels, they will be catching back up to these foreign markets.

Monday, May 26, 2014

There is a remarkably regular pattern between the Fed Funds rate and Commercial & Industrial Loans as a proportion of total bank credit:

Recovery in C&I Loans has always coincided with recovery in the effective Fed Funds rate. In fact, the Fed Funds rate tends to precede C&I Loans, slightly. So, this recovery is unique.

Corporate spreads are still a half point higher than typical recovery lows, and banks don't seem to be excessively profitable. There are plenty of reasons why rates would still be low. And, the natural short term rate was probably significantly below the zero lower bound, so there was no way to measure a recovery in short term rates. And, the banks were so hobbled, this might be a recovery that is unusually supply based, whereas previous recoveries were generally demand based.

But, this does make me wonder about the shape of interest rate movements to come. I wonder if demand for C&I Loans will be fairly inelastic even if rates go up a couple percent. If the limit to bank asset growth has been the product of some discrete risk management, capital, or regulatory limits instead of some continuous function of supply and demand of credit, maybe rates are well below their functional equilibrium levels, but it just hasn't made much difference in credit markets because of other factors.

Thursday, May 22, 2014

Here is a table of intrinsic home values, based on the present value of 50 years of rent payments. All homes are based on $12,000 in net implied rent per year. (edit - By net rent, I mean rent minus costs of ownership, like taxes & maintenance.) I am assuming that rent inflation equals the expected inflation portion of the discount rate, so the intrinsic value is completely dependent on the real portion of the discount rate. (edit - expected rent inflation should differ from location to location. In locations with higher expected rent inflation, we should see higher home prices, relative to net rents.)

The total nominal rates in these tables is a combination of the real and the inflation rates, so the nominal discount rate where inflation is 3% and the real rate is 5% is the same as the discount rate where inflation is 5% and the real rate is 3% (approx. 8% in both scenarios).

Here are the monthly mortgage payments for the same home. (I have assumed, for simplicity, that the mortgage interest rate is equal to the discount rate applied to future rent payments.)

The intrinsic value of the home is only a product of the real rate, but the mortgage payment is a product of the total nominal rate. Since the mortgage payments happen sooner, on average, than the rent payments that create the home's intrinsic value, real rates affect the value of the home more intensively than they affect the size of the mortgage payments. This has the odd effect of causing real rates and inflation premiums to have the comparatively opposite effect on mortgage payments. Higher inflation causes higher mortgage payments, but higher real rates cause lower payments.

So, the most expensive home, in terms of mortgage payments, is the home that has a 10% mortgage rate that is entirely an inflation premium. But, the home with the lowest mortgage payment is also a home with a 10% mortgage rate - the home with no inflation and 10% real rates.

This is why viewing the housing market through the lens of nominal rates is incoherent. It seemed coherent when inflation rates were high and volatile in the 1970's & 1980's, and inflation was the most influential element. Then, other factors like cyclical and demographic demand factors would have been noticeable, and since inflation was very high in the 1970's when real rates were very low, the mitigating effect of those high mortgage payments on demand masked the valuation effects of real rates.

But, the taming of inflation has exposed the effect of real rates. Over the past 20 years or so, we have gone from 8% rates (4% real + 4% inflation) to 4% rates (2% real + 2% inflation). This would lead to an intrinsic value moving from $258,000 to $377,000, with mortgage payments staying roughly the same.

Here's an example of the kinds of problems that crop up when we set public policies based on imperfect models (and they are all imperfect). If the Fed managed to push inflation expectations up to 3%, which would probably be beneficial in the current low rate context, the positive effect this would have on markets in general and home markets specifically would probably move home prices up. (I believe they are below intrinsic value now, due to the damaged credit market.) In addition, the higher inflation premium would cause the average mortgage payment to go up another 12%. If that happened, the standard "home affordability" indexes that compare mortgage payments to household incomes would trigger red flags, everyone would start yelling "bubble" and "housing inflation", and the Fed will be obliged to sucker punch us again.

Since low real rates are probably going to be around for another cycle or two, we will continue to have this phantom housing "inflation", along with high nominal levels of capital, high nominal levels of household debt, and low nominal rates. All of these artifacts of low real rates are false signals of loose monetary policy and over-expansion, and are important reasons why I expect the Fed to continue to be erroneously hawkish. Fed members even refer to their recent policy stance as loose or accommodative.

Tuesday, May 20, 2014

I have been forecasting a continuing recovery in home prices, arising out of my point of view that home prices in the 2000's weren't actually out of line with other assets, even though, at the time, I considered them to be crazy.

A Digression
I live in a neighborhood with many young families, and we would laugh back then about how none of us would have been able to afford the homes that we had all purchased a few years before. That seemed like an obvious sign at the time that the homes were overpriced. Now, I believe that it was perfectly reasonable for our homes to be too expensive for us to buy. Long term real risk-free interest rates were about 2% at the time. Baby boomers and investors who needed long-term fixed income should have owned our homes, and we should have been renting the homes from them.

This whole issue is similar to the difference between owning a AAA-rated bond and buying a bond-holding mutual fund. The bond fund is marked to market each day, so the volatility of the present value of the investment is made very clear. Individual bonds are sometimes marketed to individual investors as a source of safe, fixed income. But, the difference is mainly a matter of framing. If the investor marked that bond to market each day, it would be just as volatile as the fund. But, if the investor doesn't mark to market, then they simply see a $100 investment that pays them $4 per year every year until maturity. The cash flows are very stable.

There is a similar situation going on in real estate, except that real estate prices aren't only a mathematical product of a stated yield, so the risk factors are stated differently. I imagine my statement about real estate investments in the 2000's eliciting a reaction of incredulity - that even though I might argue that they could have been good investments, that theory clearly didn't pan out. But, that theory only didn't pan out for homeowners who were marking to market. Rent levels are fairly stable. If an investor bought a home with cash in 2005 and continued renting it throughout this period, their cash flows would have been, more or less, in line with their original expectations - much like the owner of that AAA-rated bond. And, if they had originally planned to sell that house in 2030, there is no reason to think that its eventual value will be such that their investment won't have earned some small real return over that time. (Homes don't promise a set maturity value like bonds, and so they tend to provide higher returns to compensate for that risk. In fact, I have been modeling homes as a low-risk bond holding, but maybe I should envision them more as a high dividend equity.) In any case, my point is that, eventually, in hindsight, even after all that has happened, if in 2005 you had needed a long-term inflation-hedged asset, a house will probably have suited that purpose just fine.

Home Price Forecasts

I have been looking at price to rent ratios from the various home price indexes, and it is interesting how much variation there is. Here is a graph of some price indexes, indexed to the top of the market at the end of 2005. In addition to those shown here, there is the CoreLogic series, which I believe shows similar behavior to the Case-Shiller series shown here. These series seem like the outliers, although they do seem, anecdotally, like they reflected existing home prices in major cities. To the extent that Case-Shiller is accurate, then homes seem undervalued by 40% in a functioning credit market, given expected long-term real interest rates. This might be relevant to a new speculative position that involves straightforward exposure to real estate assets.

But, if a position is going to be established by exposure to homebuilders, then the Median Sales Price of New Houses series is probably more relevant. This series was much less volatile than Case-Shiller during the boom, and was also slightly less volatile than the All-Transaction and Purchase Only home indexes from FHFA.

Oddly, the New Houses series has been much more positive since the crisis than the other series. I believe that some of this difference comes from two factors:

1) All of the home-tracking indexes (Case-Shiller and the two FHFA series) are affected by short sales and foreclosure sales that tend to be priced below the normal market level. This probably accounts for a measurable decline in stated prices throughout the crisis, currently probably amounting to less than 5% of the level that would be reported if foreclosures were not unusual.

2) The median price of new homes is not based on tracking of individual properties, so my understanding of it is that it would be affected by changing home characteristics. I have attempted to account for that by controlling for square footage, which is tracked, along with prices, by the Census Bureau. Below is the measure for square footage of new homes, and in the Price Index graph above, the light blue line is the relative Price to Rent level for Median Sales Prices of New Houses Sold, after adjusting for changing square footage. Since the end of the crisis, square footage has climbed significantly. Adjusting for this pulls the relative New Home Price To Rent measure down somewhat, but not all the way to the price measures for existing homes.

But, these adjustments put all three of the less volatile price series at around 85% of the high Price To Rent levels of the 2000's. That leaves about a 20% gain from today's prices to reach those levels again, according to each of these indexes.

In addition, the square footage adjustment to the new home price series makes that series even less volatile in the 2000's than the unadjusted measure. If this is the product of greater price-stickiness among new homes, relative to existing homes, then the high point of prices in the 2000's might still have been below the equilibrium prices. That could mean that new homes have more room to rise, relative to the other indexes. The FHFA indexes include a lot of homes in parts of the country with stagnant real estate markets. Homebuilders would tend to be in growing markets that should reflect more of the price growth that Case-Shiller is picking up. Therefore, it might be reasonable to expect the New Home price series to come in somewhere between the FHFA series and the Case-Shiller series.

Of course, if prices in the 2000's were too high, then my targets here are wrong, but accepting my basic premise, it seems as though homes are capable of a 15-20% gain to meet pre-crisis levels, at a minimum, and potentially up to more of a 30-40% gain, if the Case-Shiller index is a more accurate portrayal of the position one takes. However, treating homes as inflation-hedged cash flow instruments might only justify about a 50% gain from the mid-90's to the 2000's, which can account for the FHFA series and the new homes series, but doesn't fully justify the 100% gains in the Case-Shiller index, so it might be a bridge too far to use my premise to call for a return to the Case-Shiller highs. On the other hand, if the gains take 2 or 3 years to play out, inflation would add another 10% or so, and interest rates could rise at least another 1% while still justifying the 2000's Price to Rent ratios.

At the other extreme, new home price-to-rents, adjusted for square footage, are back at 1990's levels, so by this measure, homes could possibly call for the full 50% increase in value coming from the decreased real interest rates, but this series appears to be much less volatile than the other series, so this probably isn't a reasonable expectation. Additionally, my Price to Rent ratio for Case-Shiller seems more volatile than the ratio shown at calculatedrisk.com, although it looks he is using the same ratio. If my measures aren't capturing changes in rents and prices accurately, then there could be drift over time in the expected price level.

It still looks to me like more home price appreciation should be coming, but I don't know if I can say how much with any precision.

Monday, May 19, 2014

Core Molding Technology has been doing well. It has almost doubled since the beginning of 2013 and it's up about 30% since last summer. It is more or less proceeding as I had hoped. My thesis on this position isn't complicated. This is just a basic small cap that has been a little undervalued. Here are quarterly income numbers for the past few periods and a chart of the stock price over the past 3 years.

My main thesis here was that as CMT established more revenue outside of Navistar and PACCAR, they would increase top and bottom line numbers, but that also the added diversification would lead to some multiple expansion. I think we have already benefitted from this factor. In the period of time coming out of the recession, Navistar and PACCAR had accounted for as much as more than 80% of CMT sales. By 2014 Q1, other customers accounted for nearly 1/2 of revenues. As of 2014 Q1, Yamaha now accounts for about 10% of revenues and Volvo 25%, with more than 10% coming from other customers. After some fits and starts, they have performed well in this area.

Over the past year or so, revenues from PACCAR seem to have declined. This appears to be a transitional issue, but this is the main issue to watch, going forward. If their PACCAR business recovers, then all the pieces seem to be in place for a valuation in the high teens to $20 range. If not, then it may be prudent to take profits in the current range.

This is a decent position, but it isn't going to provide any sort of moonshot return.

Thursday, May 15, 2014

Interest on Reserves in 2008 - Highly Contractionary
I was reading this paper from Peter Ireland about Interest on Reserves (IOR). Reading that paper, and thinking through the effects we should expect from IOR, I am thinking that the Fed Funds Rate (FFR) is still the overwhelming factor with regard to monetary policy. If I have his argument correct, given the current level of reserves, a rising FFR along with a rising IOR rate should basically have the same effect as a rising FFR in an environment where there weren't excess reserves. If there weren't excess reserves, I imagine that IOR could move around below FFR without much effect on the money supply. So, it appears that they can use IOR to manage the reduction in the Fed balance sheet. But, it seems to me that the level of FFR relative to natural interest rates would work basically the same way that it has without IOR.

This leaves the question, however, of whether the implementation of IOR in 2008 was that contractionary to begin with. Generally, IOR is considered to be a floor for FFR because if IOR was higher than FFR, banks could borrow at the low FFR and hold it as reserves, pocketing the difference in rates. They would bid the FFR up to a level near the IOR rate, in that case.

In October 2008, the Fed implemented IOR, and over the course of a month, ratcheted up the IOR rate until it was equal to the FFR target. But, throughout this period, the effective federal funds rate was volatile, and tended to run below the FFR target. So, from November 5, when the Fed pegged the IOR rate to the FFR, until December 16, when the FFR (along with IOR) was finally reduced to 0.25%, the effective FFR was running 0.5% to 0.75% below the IOR rate. During this time, the Fed had accumulated a substantial amount of non-traditional assets, but it was not purchasing treasuries, and in fact would not start adding to securities held outright until March 2009.

There were so many things going on at the time with the Fed balance sheet, and I am no expert on the micro structure of trades between the Fed and commercial banks. But, something in November and December 2008 was pushing the effective FFR well below the IOR rate while excess reserves ballooned. It looks to me like the Fed should have pushed the FFR to 0% in October with no IOR, since the market risk free rate was in free fall, and the economy was desperate for cash. Instead, the Fed sucked all the panicked cash out of the economy with IOR above the market risk free rate, to the tune of more than half a trillion dollars.

IOR and Excess Reserves at the End of QE

With regard to the amount of excess reserves currently outstanding, I wonder if there is a point where rising short term rates with stable IOR rates would actually be expansionary. Further, if reserves aren't the only constraint on bank lending, then I think short term rates could rise even while excess reserves remain in the system. With FFR, IOR, and the level of securities on the Fed balance sheet, there are several moving parts to consider now, but I think, regardless of Fed policy in the very short term, natural short term interest rates might behave fairly typically as the economy continues to recover. It looks like the Fed is planning on raising IOR and FFR together. But, normally a rising FFR rate resulting from the Fed selling securities would be contractionary. In the current environment, if the Fed raised FFR but held IOR constant, some of the sterile excess reserves at the banks would be injected into the economy, so that a rising FFR resulting from some Fed selling could still be expansionary. If this is the case, then the liquidity effect of Fed open market operations would have a very different shape in the context of high excess reserves.

I'm not a banking expert, but it seems like if capital constraints on the banks led to an increase in short term interest rates while reserves remained high, deposit interest rates would remain low, incentivizing depositors to purchase securitized assets from the banks or loan funds outside the banks until the interest rate, new bank assets, and reserve levels reached a new equilibrium. Peek and Rosengren at the Boston Fed show that for capital constrained banks, loans can expand in response to monetary tightening, or at least that capital constrained banks will not markedly change their credit activity in response to monetary policy. Is it possible that velocity would be self-correcting as excess reserves decline?

It seems unlikely for the expansionary counter-effect to be greater than the original contractionary effect of reduced reserves. But, if I imagine an extreme world with $15 trillion in excess reserves with only $1 trillion in treasuries left in private hands, it seems clear to me that a rise in interest rates due to Fed OMO could happen with a large amount of reserves still in place, leading to a strong increase in credit and velocity. So, at some quantity of excess reserves, a reduction in the Fed's asset base must be expansionary.

I had been wondering if rates would rise slowly as we leave the zero lower bound, but now I am starting to wonder if this context, market rates could rise, which would require the Fed to either overshoot the FFR or raise IOR rates along with FFR in order to counter these odd expansionary effects. If that is the case, there shouldn't be a drag on the rise in short term rates - at worst they would rise at a pace typical of past recoveries.

Please let me know in the comments if I'm completely out of my element here, but be gentle with me.

(T)he failure of young consumers, and particularly the comparatively skilled young consumers of our student loan group, to re-enter the housing market remains a puzzle. Many factors could be contributing to this phenomenon, including growing student debt balances, limited access to credit, lowered expectations for future earnings, and perhaps even a cultural shift by which young people—whether they went to college or not—are deferring home purchases. Whatever the cause of student borrowers’ reticence, the housing market rebound of 2013 appears to have proceeded without the help of this skilled set of young buyers.

This is good news, and it's a good example of the wisdom of markets. With real long term interest rates at 1%, home prices should be high and volatile. Homes are very bond-like in this environment, and, speaking strictly from a portfolio construction point of view, they have no place in a young person's portfolio. Young families should size-down, rent, and put their money in the stock market. In 20 years, when the baby boomers are selling their homes and long term real rates are at 4%, then these young families should buy.

It might be a good rule of thumb for portfolio management for non-boomers to just ask, "What do the boomers need to hold", and then take the opposite position.

Homes have always been a good investment for just about everyone who could arrange the financing. They are still a great investment for people who need bond-like exposure (baby boomers) but they are not currently a good investment for everyone. The market represented by young families has figured this out, even if individual families, social convention, regulators, the GSE's, and the New York Fed haven't.

Wednesday, May 14, 2014

Here are the graphs of the estimated escape from the zero lower bound, inferred from treasury yields. The schedule of the escape continues apace, in the face of the taper, suggesting that we might finally be heading back to normalcy.

The first graph is the expected date of the first short term rate increase on a stationary calendar.

The second graph is the expected date of the first short term rate increase, measured in number of years from present. As hopeful as this looks, it's also a reminder that we are basically just getting back to where we were 3 years ago, when QE2 ended. How much further into a recovery would we be today if QE2 had been maintained until sustainable inflation pressures were established?

Monday, May 12, 2014

April numbers are out in the Fed's H.8 report of bank balance sheets. Bank credit is smokin'. The engines are revving in this economy. Seasonally adjusted annualized rates of growth are moving up across categories.

Friday, May 9, 2014

Here are a couple of graphs looking at past interest rate behavior. This first one is a variant of the Taylor Rule. It came back above 0% in July, and with the recent drop in the unemployment rate, will signal a target rate between 1.5% and 2% for April, depending on the April inflation level, and conservative expectations of inflation and unemployment should add about 1% a year to this indicator.

The second graph compares the actual Fed Funds rate to a simple forecast of the Fed Funds rate, using the growth rate of Commercial & Industrial Loans and inflation. The model uses the period through 1990, so the last 24 years are out of sample. Again, this shows fairly predictable movement until recently, with a current forecast rate of more than 4%.

The third graph compares corporate spreads to the Fed Funds rate. If corporate credit spreads continue to decline another 1/2 point or so, they would be where, typically, short term risk free rates would start to rise. Note, that spreads are still fairly wide, despite all the chatter about investors reaching for yield.

Now, there clearly has been a shift in these relationships in the past 5 years, so we shouldn't expect to see perfect co-movement. But, this does point to a potential return to normalcy. I do wonder if some of the recent debate among economists about how increasing interest rates could, counterintuitively, be inflationary, could be on to something in this context. If banks ceased to be strictly capital constrained, and the Fed cut interest on reserves (IOR) to 0% and started selling treasuries, banks would be highly incentivized to convert their cash reserves into credit. The end result of those processes could be expansionary, depending on the relative quantities of Fed assets and bank reserves that ended up moving.

It's hard for me to wrap my head around all the possible ramifications of the current Fed position. It seems like, regarding interest rates as a standalone issue, a lot depends simply on the mechanics of monetary policy chosen by the Fed over the near term. My impression is that they intend to kind of sterilize the excess reserves and slowly reduce them in a way that is intended to have minimal cyclical effects. Please correct me in the comments if anyone has contrary knowledge.

Side note on IOR:
1) I disagree with the notion that IOR is a giveaway to the banks. I see the banks as having an operational balance sheet apart from the items related to the excess reserves. Regarding those parts of their balance sheets, there is some set of competitive forces that is leading to an equilibrium level of total profits. Now, due to Fed activity, the banks have $2.5 trillion in cash, which is earning some minimum level of interest, and they also have an additional $2.5 trillion in deposits, on which they are paying some minimum level of interest. I don't see any reason to expect there to be any significant net gain to the banks from these extra assets and liabilities. If the competitive landscape led to $x profits without the excess reserves, that same landscape should be expected to lead to $x profits with the reserves, plus some insignificant extra profit for the trouble of servicing the accounts. Now, considering where we are, the excess reserves probably benefit everyone to the extent that they represent accommodative monetary policy, but I just don't see the direct transfer of cash to the banks adding up to much.

Thursday, May 8, 2014

Bank balance sheets continue to explode as QE3 tapers. Here is a comparison of excess reserves at the Fed with Loans and Leases in Bank Credit at Commercial Banks:

I view the QE programs as a type of bank credit supplement, in the form of cash. The Fed is a sort of bank that can only take deposits through other banks, so the excess cash and its corresponding deposits sit on commercial bank balance sheets, but are totally disconnected from the banks' operational balance sheets. I have speculated that the inverse movement of these quantities might suggest that QE has served as funding for profitable investment, crowding out the banks' supply of credit for a limited supply of viable investments. Now that QE is tapering, banks have a pent up supply of capital available to extend credit as a replacement for the cash that was previously being provided through QE3. Bank credit has suddenly begun expanding at a rate that more than makes up for the decline in QE cash.

In a way, it is simply a semantic difference. Cash rich non-banks have been buying up bank loans and real estate mostly as a result of this fact that credit since the fall of 2012 has been coming into the economy in the form of QE cash instead of in the form of bank credit. Here is a measure, from soberlook.com of the collateralized loan market. Notice that it seems to rise along with QE3. And, in the next graph, also from soberlook.com, we see inflows declining along with the taper.

It seems to me that if the Fed can arrange a mechanism where they eventually trade the banks treasuries in exchange for excess reserves, while minimizing transaction mechanisms that would temporarily pull cash out of the economy (a reverse hot potato effect) the Fed's inflated balance sheet is relatively benign and mostly unconnected to the eventual position of monetary policy.

Wednesday, May 7, 2014

Hutchinson Technology is really trying my patience. They just keep pushing along in that gray area between success and failure, with plausible excuses. Now it looks like they will hit 130 million units, maybe in 2Q 2015. Nine months ago, the hoped-for date was 4Q 2014.

It's not a problem of losing share. It's just that the new programs which should increase share are taking longer to ramp than expected. Having made that adjustment, things are moving about where they should be. Gross margins, even at these low volumes are nearing 10% as production moves to Thailand.

This valuation can move quickly with margin improvements, margin improvements can move quickly with volume, and volume can change quickly. And, all of these things can happen with just a 5% gain in hard drive sales and a 5% market share gain, both of which could legitimately happen in a few quarters. And, they have made progress since the Thai floods in 2011. Losses are significantly lower. The previous quarter was the best quarter since the floods. If we had seen a positive shift of 15 million units this quarter instead of a negative shift, we'd be at breakeven now. So, am I being greedy, waiting for the big payoff that's never going to come? Or am I being greedy, missing the obvious improvements that the firm has seen, because I'm being impatient?

In a couple of years, this will either look like a brilliant position, or it will be a position where I was being obtuse and I'll wonder why I didn't see how obvious it was that this wasn't panning out.

Some of these are easy and some, like this one, are hard. The problem is that the hard ones frequently work out ok in the end. The ones that seem easy are probably mostly a product of lucky timing, where I just happened to find the company right before things turned positive, but that if I had found it 2 years earlier, I would have found it just as compelling and I would have been frustrated and doubting.

For now, I am keeping this position on, but if the options market becomes a little more efficiently priced, I will continue to look for ways to change my exposure to call options.

Monday, May 5, 2014

I have previously compared the historical level of minimum wage employment with the relative level of the minimum wage, in an effort to forecast employment loss resulting from the minimum wage. I had used the Average Hourly Earnings of Production and Non-supervisory Employees series as my average wage basis. But, over time, this series appears to have lagged other indicators of wage growth, and the effect on my analysis was to create a positive drift in the ratio of minimum wages to average wages.

I have looked at this analysis again, substituting the DOL's Compensation per Hour index. This doesn't have the negative drift over time that AHETPI does, and it produces a much stronger linear relationship between relative minimum wage and the proportion of the labor force working at or under the minimum wage.

This relationship is surprisingly linear, but it doesn't necessarily suggest job losses without a job level to use as a comparison. Luckily, there are available measures of the number of workers in a non-minimum wage context to compare this with.

One comes from The Economic Policy Institute. They issued a report on the minimum wage that included a count of the current number of workers earning $10.10 or less - about 21.3 million, or 13.5% of the labor force. I can compare this number to the number of actual minimum wage workers measured the last time the minimum wage was at that relative level. If the actual number of workers was significantly less than the current number, that would suggest that the high minimum wage caused some unemployment.

Here is the relationship, using Compensation per Hour.

The relationship is very tight, and the number of workers was much lower than 13.5%. It is highly unrealistic to think that the level of employment at minimum wage will deviate from the long term trend to anywhere near what it would need to in order to assume that there will be no job loss. This relationship can be used to estimate the number of job losses that a minimum wage increase will cause.

(Note that the relationship levels out below about 25% of the average hourly compensation, which suggests that this is essentially the natural minimum wage level. It also suggests that the initial MW hike in 2007 probably had negligible disemployment effects, but that the 2008 and 2009 hikes had more typical effects.)

One reply to this problem would be that a minimum wage hike would lead employers to boost the wages of some workers to levels slightly above the new minimum wage, and that would cause the number of measured workers at or below a minimum wage of $10.10 to be less than the current number of measured workers at $10.10. But (1) it is implausible to imagine that two thirds of workers currently earning between $10.10 and $7.25 would see wages increased to above the new MW level. And (2) this would create a sort of asymmetrical reaction to MW hikes, where we would expect to see a deviation from the long term trend as employers made relative adjustments to workers' wages after a MW wage shock, but then the proportion of workers would revert back toward the trend as the new minimum wage level aged and declined in real terms.

The relationship we do see is very linear. As the real MW level decreases over time, the number of MW workers follows the trend closely, and when MW was raised in 1990-91, 1996-97, and 2007-09, the number of workers moved right back up the trendline, with very little deviation. This suggests a surprisingly efficient labor market.

As one last exercise, I have used a previous regression of the employment-population ratio against RGDP and minimum wage levels to estimate the total potential MW labor force. I had found a correlation of the loss of .168% in EPR for each 1% rise in the ratio of the minimum wage to the average wage. I added this estimate of the number of job losers to the historical measured number of MW workers. (In all of these graphs, I am using the total number of workers at or below minimum wage.)

My regression would estimate a total decrease in employment of 4.5 million if the minimum wage were raised from $7.25 to $10.10 today. That would leave 7 million workers unaccounted for, who could be workers who start out below the new minimum but receive raises to above the new minimum upon implementation, or could be unemployed workers that weren't counted by my regression analysis. My regression was based on 2-year periods of serial MW-hikes, so the changes it was measuring would have included some period of time following the last hikes of a series where employment would have been recovering. This would cause it to understate disemployment. I think it might be realistic to expect that 7 million workers to be split between mostly workers who are bumped to above the new MW and some additional workers who would lose employment.

One could trifle with the precise estimates I am using, but I don't see how anyone could look at this very linear and long-term relationship, compare it to the current number of workers making $10.10 or less, and dismiss the expectation of significant job losses.

﻿One note concerning the 21.3 million workers at $10.10 or less, estimated by EPI: This is based on their assumption of no job losses from MW. If one does accept my analysis here that the MW does cause job losses, then one would add the additional 1.3 million workers who are currently (as of 2012 data) unemployed because of MW to the total number of potential workers at $10.10 or less. That would increase the EPI estimate of current sub-$10.10 workers to 22.6 million workers, and it would leave 8.3 million workers unaccounted for instead of 7 million workers.

Another follow up point: My regression measured unemployment across the economy. The graph above is measuring only MW workers. This difference could be interpreted in several ways. One could wonder if my regression is undercounting the job losses by even more than it seems. One could also suggest that the MW hike would cause 12.8 million minimum wage jobs to disappear, but that substitutions across the economy would lead to the creation of 12.8 higher paying jobs to replace them.

Minor tweaks in interpretations can get us from point A to point Z, but this relationship looks regular enough and compelling enough that those interpretations have a pretty big gap to fill.

Friday, May 2, 2014

Previously I had modeled long term unemployment by comparing long term unemployment durations to short term unemployment durations. Here I have modeled long term unemployment rates as a linear combination of the shorter duration unemployment rates, to compare the results to the other model. The results turn out to be similar.

Here is the 66 year history of the model. The specification is based on the relationship from 1948 to 1991. The deviations of the model in 1992 and 2002 coincide with the previous two recessions and the previous two EUI episodes, which were much less generous than the recent episode.

Next is the difference between the modeled Long Term Unemployment Rate (over 26 weeks) and the actual LT Unemployment Rate. This is similar to the numbers I have arrived at through other methods. And, I believe the story is similar for the current labor market. The very long term unemployed seem to have a linear behavior that is not related to EUI policy at this point, because this group had probably mostly already timed out of the program. As with my previous estimates, this estimate suggests that this group is shrinking by about 0.05% of the labor force each month. So, if this continues, the unemployment rate should continue to decline by about 0.6% over the next year.

I think that this method does help show how the end of EUI has filtered through to recent declines in the unemployment rate. Beginning in the fall of 2013, unemployment durations of 5 to 26 weeks acquired a new, sharply declining trend, which has continued through April.

Durations from 15 to 26 weeks might continue to decline by about 300,000 (about 0.2%) over the next few months, but that would bring it near to probable trough levels. These recent declines in short term unemployment should filter through to long term (>26 week) unemployment, with 0.1 - 0.2% in future declines already in motion and another 0.2 - 0.3% decline possible if the 15-26 week category continues to decline.

I think this realistically adds up to declines by the end of 2014 of about a 0.4% UE decrease from the VLT group and another 0.4% UE decrease from the trends that began in late 2013 in shorter duration categories and the expected declines those trends should produce in the long term category. That puts us at 5.5% unemployment by the end of 2014.

It is possible that these trends will dissipate, but there is no evidence of that happening now. And there might be some snap-back from the April number, but I don't see any reason to expect anything above, say 6.4%, even figuring on some noise over the next couple of months as the downtrend continues.

Labor Force Participation

The Employment to Population Ratio has shown some slight momentum over the past couple of years, but labor force participation continues to show weakness. This doesn't quite fit with my amended theory of the EUI. I would have expected some weakness coming out of EUI as some relatively small proportion of long-term unemployed would have exited EUI by exiting the labor force. However, if there is this bifurcation among long term unemployed, and if the end of EUI didn't really affected the behavior of the very long term unemployed, I wouldn't have expected there to have been much LFP weakness. If the end of EUI mostly caused an exit from unemployment among unemployment durations of, say, 5 to 40 weeks, I would have expected a smaller portion of those beneficiaries to have left the labor force. But, there does seem to be some weakness in LFP coincident with the end of EUI.

We might continue to see more of this weakness over the next few months before LFP finally settles back into a direction parallel to (or reverting to) the demographically adjusted trend.

The noise went back the other direction this month & took us all the way to 6.3%. Let's take a look at the parts & pieces.

First is unemployment by duration. I suspect there was some statistical noise this month that moved unemployment down. Here we can see that unemployment declined across durations. But, all the excess unemployment is currently in the ">26 weeks" category. The other categories are pretty much at normal levels. They might have a few 100,000 to give between now and the cyclical peak, almost entirely from the 15-26 week category. (As a percentage of the labor force, that dip in 0-4 week unemployment in December was the lowest level ever recorded.) So, while it's a good sign to see them declining, there is likely to be some bounce-back there in the coming months. Also, keep this is mind when reading the inevitable misreadings of statistical noise as desperate workers giving up. That story doesn't match up well with the significant declines in short-duration unemployment.

That statistical noise looks like it helped the ">26 week" category, too. I am not seeing any unusual decline in my estimated number of very long term unemployed this month, so I don't believe that this month's decline is strong evidence of an EUI effect, although the trends remain relatively positive, in general. Most of the decline in unemployment over the past few months has been among workers under 45 years old. There appears to be a correlation between older workers, EUI, and very long term unemployment, so the relatively small decline in unemployment among older workers also suggests that the unemployment decline is not particularly related to the termination of EUI.

I have been watching the churn in long term unemployment. The gross number of people leaving long term unemployment over the past 3 months has been remaining strong at about 2 million. It dipped down to about 1.8 million last month. It recovered to about 1.9 million this month, so it didn't get all the way back to 2 million, but at least it's heading in the right direction. January wasn't an easy month to compare against, either. If this flow remains at 2 million a quarter, long term unemployment should be below 3 million by July.

It's a similar story if we look at this flow as a percentage. It bounced back this month to above 35%, and the moving average continues to improve, but I would have liked to have seen a stronger shift in the trend coming out of the end of EUI. As I mentioned yesterday, though, the problematic portion of very long term duration unemployment probably did not have much of a direct involvement with EUI by the end of 2013. The re-engagement of that group of workers with the labor force will probably be a little more complicated and slow than we would like. I still expect to see an acceleration in the exits from long term unemployment, but this is a process that will continue for many months. Here's a graph of the duration categories back to 2006, for reference. Keep in mind that population growth and demographic shifts probably will keep the longer duration unemployment levels from declining all the way back down to 2006 levels.

In the comparison between continued unemployment claims and the unemployment rate, this month obviously pulled us back toward the long term relationship. But, as we can see in the graph, there is a long way to go, and this month's movement, in terms of this relationship, was not unusual. The question will be how quickly this convergence happens. It's hard to see that in this graph.

Here's a graph of the ratio over time. This shows a few interesting things. First, we can see how when a recession first affects the labor market, the ratio decreases, because an uptick in involuntary unemployment creates a sharp increase in unemployment claims. The ratio then increases as sclerosis in the labor market leads to longer unemployment durations, so that the unemployment rate includes many workers who are not collecting standard UI benefits. Then, the ratio declines back to typical levels under 3.0 as the labor market recovers. Second, it is interesting to see that in this cycle, EUI was implemented before there was the typical cyclical increase in standard unemployment insurance claims. Third, it would be unusual to see a decline to the level that would correspond to full recovery in less than about 18 months, at the soonest. But, the current relationship is highly unusual, so it wouldn't be out of the question to see the return to a normal ratio level happen more quickly than it has in the past.

It really is pitiful, the extent to which the federal government damaged the labor market in 2008. In June, they instituted EUI, which would have the effect of making the labor market less flexible because it would have some marginal influence on sticky wages. Then, in July, they instituted the second in a string of minimum wage hikes. So, in a context where Congress is clearly concerned about labor market health, they force a wage hike on the most vulnerable workers. Talk about sticky wages. Then, at the Fed meeting in September - a meeting where FOMC members explicitly state that they believe that EUI has already had a negative effect on the unemployment rate, the committee decides to inflict the labor market that has been freshly seasoned with significant wage inflexibility with a whopping deflationary shock.

Flows

Looking at flows, we can see some of the likely statistical favors this month's employment report received. In every single pair of flows, this month's movement was favorable. These tend to be very noisy, so this was likely a one-time improvement. But, it is important to keep in mind that all these flow pairs are going in the right direction, and the previous 3 months have had noise-movements in the other direction, so that it is likely that 6.3% is a legitimate reading and the unusual movement was the result of the movements in the other direction in previous months.

Even with the drop in "NtoE", the cumulative flow from NtoE over the past 4 months is still very high. The flows between U and E (green and blue) have been showing tremendous strength, and this month's positive movement is part of a well established and positive trend. The decrease from "NtoU" follows several months of unusually positive readings compared to the longer decreasing trend. And, this is counterintuitive, but a decrease in this flow is bullish. We tend to see this through a narrative of desperate workers coming into the labor force. But, it is just as likely that a decrease is the result of a lack of desire for work among those who are not in the labor force. The fact that this pair of flows has a clear pattern of being low during booms and increasing during busts strongly suggests that something like the positive interpretation is dominant. This set of flows is the one set that has been unusually high relative to other measures of the labor market - probably due in part to EUI - so a decline in this flow pair is something we should expect after the end of EUI. The complicated relationship between EUI and very long term unemployment is evidenced by the high level of this flow pair compared to historical levels. I'm disappointed that we haven't seen more decline in this flow pair since the end of the year.

Lastly, looking at the flows into and out of unemployment, we can see a little bit each of legitimate strength and statistical noise. The extreme decline in unemployment owes partly to the unusual decline in the net "NtoU" movement. But, we can see that this net flow has been unusually high since December. The trend in this net flow has been flat since the beginning of 2011, and the cumulative net flow of the last few months is roughly in line with that trend. Net flows from Unemployment to Employment have been trending up nicely since the beginning of 2011, which is a sign that the labor market is actually gaining momentum. This month had a strong net flow here this month, but it wasn't highly divergent from trend.

I think the totality of these indicators suggests that 6.3% as of April 2014 is a good estimate of long term trends in the labor market. Labor markets look relatively strong even though there is no clear indication yet of an EUI-related 2014 boost.

Thursday, May 1, 2014

Here is an update on the unemployment insurance claims numbers. Both measures bounced up a bit this week, so the trend going through April doesn't look as strong as it did last week, but continuing claims still seems to have a promising trend.

Here is an amended version of the other graph I put together the other day, comparing the unemployment rate with the rate of unemployment insurance (using civilian labor force as the denominator). Using the higher continuing claims level from this week, the unemployment level that would be parallel to trend would be between 6.5% and 6.6%. (Last week it would have been near 6.4%.) Of course, we should expect the unemployment rate to approach the lower typical level as the economy recovers, so it should do better than just moving parallel to the normal trend, though there will be noise from month to month.

I'm also trying to get an idea about the mysterious long duration unemployed group. This is not a sophisticated model, but I'm just trying to work out a basic idea of the data here. In mid-2011, the average duration of unemployment for people unemployed more than 26 weeks leveled out at around 80 weeks, and has remained at that level, even as the total number of long term unemployed workers has declined. I am using a simple assumption that, starting around 2011, unemployment can be divided into two groups. Short term unemployment began to recover to normal levels, and for these workers who were unemployed for more than 14 weeks, each quarter approximately 50% of them exited the unemployment rolls. Additionally, there was a second group of very long term unemployed workers who were more persistently unemployed. This group appears to have declined in a somewhat linear pattern, averaging about 80,000 workers per month.

So, by March 2014, there were about 3.7 million workers who had been unemployed for more than 26 weeks. About 2.1 million were in the very long term unemployed group, roughly averaging 100 weeks of unemployment. And, about 1.6 million were leaving unemployment at roughly typical rates for a normal economy, with an average unemployment duration of about 60 weeks.

Even in a typical labor economy, some workers have durations of unemployment over 26 weeks. So, if we assume that Emergency Unemployment Insurance above 26 weeks has no effect on their subsequent duration of unemployment, we can assume that, given the availability of EUI, a typical proportion of workers would take payments from EUI. This graph compares the reported number of EUI beneficiaries (blue) to my estimate of the very long term group of unemployed (red). In addition, I estimate the number of EUI beneficiaries who are part of that very long term persistently unemployed group (green). So, reading from bottom to top, the green line is the number of VLT unemployed who are receiving EUI. From the green to the blue line is the number of unemployed workers who would be eligible for EUI in a typically functioning labor market (with 50% quarterly turnover, as described above). And from the green to the red line is the estimated number of VLT unemployed who are not receiving EUI.

As the following graph demonstrates, the behavior of the long term unemployed has been very peculiar this cycle, coincidental with the unprecedented level of EUI benefits. There has been a disconnect from a relationship of employment durations that is decades old. EUI created significant frictions in long duration unemployment. Some of this could have been from subtle effects on reservation wages, simple incentives for workers with some discretion, hysteresis among former beneficiaries, etc.

It is difficult to determine what we could expect from the current unemployed cohort. If my graph above is accurate, then by the time that EUI was terminated, the unemployed workers who were still beneficiaries were mostly not members of the persistent very long term group of unemployed. By 2014, the very long term unemployed lacked any direct connection to the remaining EUI program. This would suggest that the end of the program may not have an immediate, direct impact on the very long term unemployed. And this group is essentially the entire reason why the current unemployment rate is higher than normal recovery levels. So, my optimism for unemployment in the first half of 2014 may have been misplaced.
The number of very long term unemployed who were not EUI beneficiaries (either because they timed out of the program or because they hadn't been eligible) has been pretty level at about 1.5 million for several years. In effect, broadly speaking, each month, 80,000 VLT unemployed who were not on EUI would leave unemployed status, but they would be replaced by another 80,000 unemployed coming out of EUI. But, if this was the case, and there was a churn of workers through EUI, then we should have seen the net number of VLT unemployed leaving unemployment increase as the number of EUI recipients declined. This didn't happen. The decline in VLT workers has remained pretty linear, about 80,000 per month.

So, it seems like we may not see a direct impact from the termination of EUI. And, it's possible that either unemployment will continue to decline linearly or will decline less quickly if there are a large number of permanently unemployed workers in the VLT group. However, I think there could be a complex set of ingredients here that still could lead to a decline in VLT unemployment as we leave EUI and proceed through 2014.

Here is a graph of the gross number of workers who leave LT unemployment each quarter. (This is the starting number of 15+ week unemployed minus the 26+ week unemployed who remain unemployed 3 months later.) If my pessimistic scenarios above were true, we should have seen this flow decline as EUI wound down, if the remaining VLT unemployed were more persistently unemployed. This month should add interesting information here. This flow actually stabilized at around 2 million workers during the last year. (This is for all workers, so about 1.6 million of these workers are workers in the recovered economy who have flowed into and back out of unemployment, and the remaining workers in this flow would be coming out of the VLT group.) Last month, this flow dipped down to 1.8 million, but these are noisy data. So, if this flow continues to decline toward 1.6 million, this could mean that the VLT group will be very persistent. If this flow recovers back to 2 million, then this should bode very well for the labor market. Even if EUI was only pulling in a couple hundred thousand workers into a VLT unemployment context, the removal of that program would mean that the net 400,000 workers leaving long term unemployment each quarter would affect the bottom line unemployment figure, and we would be seeing sharper decline in the net remaining number of VLT unemployed.

I think the factor that could make this true would be the inaccuracy of my assumption above that continued EUI was not affecting the long term duration of unemployment for the workers who have recently been becoming beneficiaries. It is possible that, even though much of the labor market is back to normal, EUI was continuing to have an inflationary effect on the duration of unemployment for the workers who did end up in the program. Even at the end of 2013, the program might have been feeding the VLT unemployment problem, and some of those EUI beneficiaries were being converted into VLT unemployed as they were exposed to the perverse incentives of the program.

Regarding the gross flow out of LT unemployment, all else equal, if that flow declines down to 1.7 million in the April report, the unemployment rate will be at 6.7 6.6%, and if it recovers to 2 million, the unemployment rate will be 6.5 6.4%. The over/under on this month's report could indicate what we might expect as we move through the year.

Paul Krugman posted this Fred graph on Tuesday. (He included just the construction unemployment rate. I have added the broader unemployment rate for reference.)

I noticed that, after 5 years of stair-stepping down, construction unemployment has finally reached normalcy. (Strangely, Krugman's reason for posting the graph was to justify public infrastructure spending, because: "It also wouldn’t divert labor from other uses: unemployment among contraction (sic) workers remains high: So it’s deeply irresponsible NOT to spend this money...". Weird. There might be ways to make that argument, but this graph doesn't seem like it's one of them.)

I noticed that the peak of construction unemployment this winter roughly matched the peak construction unemployment of 2004-2005, when unemployment was around 5.5%. This is another great sign that unemployment is closer to full recovery than it might first appear.

Then, I looked at construction employment, and this is what I saw. Total employment is just now surpassing the previous peak. But, even though construction unemployment is back to normal, construction employment is still more than 1.5 million below the peak. That accounts for most of the remaining excess unemployed workers...except that they aren't showing up as unemployed construction workers. So, almost all of the decline in construction unemployment seems to have come from labor transitions to other industries or out of the labor force.

The extreme behavior of construction employment has been a point in the structural vs. demand debate. This would appear to be a point scored for the structural side. But, I don't think it necessarily is. For starters, construction employment is still down at 1997 levels, and I don't think most supporters of the theory that we had too much construction would say that the proper level is back at 1997. But, further, it seems plausible to me that the sharp liquidity crisis that the Fed created along with the resulting credit crisis coming out of the crippled banking sector, could have been especially damaging to a sector that relies on long term investments and a liquid and functional credit market. I'm not sure it's so easy to separate supply and demand effects into nice, separate baskets here.

It will be interesting to see if construction employment accelerates, if we see a return of growth in real estate loans at the commercial banks. Surely, construction is due, at this late date, for a rebound.